Process Modeling Engineer

Position: Process Modeling Engineer
Location: Corning, NY (100% Onsite)

Qualifications:

• Minimum of 4-6 years of experience in process modeling, simulation, or computational engineering within a manufacturing or industrial environment.
  Master s degree in Mechanical Engineering, Chemical Engineering, Materials Science, or related discipline (PhD preferred).
  Strong experience with Finite Element Analysis (FEA), computational modeling, or process simulation tools (Abaqus, Ansys, COMSOL, or similar).
  Solid understanding of solid mechanics, heat transfer, fluid flow, and material behavior under various loading conditions.
  Proficiency in programming and scripting languages such as Python or MATLAB for model development and data analysis.
  Experience working with glass, ceramics, polymers, thin films, or advanced materials is preferred.
  Strong analytical, mathematical, and problem-solving skills.
  Excellent written and verbal communication skills with the ability to present technical findings to cross-functional teams.

Key Responsibilities:

• Develop and execute computational models to simulate manufacturing processes and predict product performance.
  Utilize FEA, BEM, or other numerical modeling techniques to analyze stress, strain, thermal effects, and failure mechanisms.
  Validate simulation models through experimental data and recommend design or process improvements.
  Collaborate with R&D, product engineering, and manufacturing teams to optimize product attributes and reduce production costs.
  Develop new analytical tools or enhance existing modeling frameworks to improve simulation accuracy and efficiency.
  Lead technical investigations related to process deviations, product failures, or customer concerns.
  Prepare detailed technical reports, documentation, and presentations summarizing modeling methodologies and results.
  Support product qualification efforts by recommending appropriate testing strategies and interpreting performance data.
  Stay updated on emerging modeling techniques and technologies to drive continuous improvement.